Transcript indian customs edi system - Directorate of Valuation

WELCOME TO
EXPORT COMMODITY DATABASE
(ECDB )
Presentation by
DIRECTORATE GENERAL OF
VALUATION
OBJECTIVES
· A comprehensive Database on Exports focusing on Valuation.
· Capture of export data in a standardized format on a daily basis from
all customs stations.
· Consolidation and analysis electronically by DOV to identify potential
cases of valuation fraud
· Export Valuation Tool and Decision Support System.
· Check abuse of export incentive schemes based on export value.
· Check unscrupulous exporters going to smaller
overvalue goods.
stations
to
Compilation of statistical reports and returns concerning export
valuation
PHASE I
·
·
Essential data fields identified and standardised.
Software designed in consultation with NIC to extract export data
from EDI stations.
·
Software installed at EDI stations for data extraction as EOD.
·
Export data transmitted to DOV from EDI stations via ICENET.
·
Data is merged at DOV into a single data source and unit values
determined.
·
Display format in Access and designed query Module for easy
access of data.
Internet version was prepared and made available on DOV website in
Nov 2004.
www.dov.gov.in
ECDB DISPLAY (Phase I)
DATA ANAYSIS SOFTWARE
·
CDAC was assigned contract as per Ministry’s approval.
·
Technical requirement document was prepared by DOV.
·
Consultation with custom stations and feedback taken.
·
DOV interactions with technical teams set up in CDAC for software development.
·
Trials and evaluations by DOV.
·
Demonstrations to field officers at Mumbai Customs Zone.
·
Modifications based on feedback.
·
Final version is ready for launching.
·
Data analysis performed by clustering the raw data under selected set of fields for
desired period.
·
Work out weighted average for each cluster and the standard deviation for each
record within the cluster.
·
Sum of Weighted Average and Standard Deviation for that cluster gives the value
limit for determining outliers.
·
Outliers are marked for records whose Unit assessed value is outside the limit.
SOFTWARE FEATURES
·
·
Consolidation of raw data.
Selection of raw data for analysis (period)
·
Selection of desired features such as
description, HS Code, UQC, COD, Export
Incentive Scheme Codes.
·
Description by keywords prepared by software
based on data mining.
·
Clustering mechanism used for data analysis.
Flexibility to choose various parameters for data
analysis and DOV studies.
FEEDING FILTERING MECH
SENSITIVE COMMODITIES
•
· Data analysis to be done for sensitive goods
•
·
Data filtering mechanism applied to prepare
sensitive list
•
· Selection of sensitive commodities based on:
•
·
DEPB Schedule numbers,
•
·
Drawback Serial numbers,
•
·
DFRC Serial numbers
•
Entries having value cap and specific rates excluded
•
· Selected commodities are grouped under HS Codes
•
· Sensitive data selected as above is about 12% of
export records.
FEEDING CLUST MECH
PERFORMING ANALYSIS
•
•
·
Data analysis performed by clustering the raw
data under selected set of fields for desired period.
•
·
Works out weighted average for each cluster
and standard deviation for each record within cluster.
•
·
Sum of Weighted Average and Standard
Deviation for that cluster prescribed as the value limit
for determining outliers.
•
Outliers are marked for records whose Unit assessed
value is above the limit.
•
OUT PUT
•
·
•
•
·
·
data.
·
Analyzed data to be dispatched to EDI stations via
ICENET
·
CDs with previous data of 3 months to all stations
·
Local databases to be set up by Customs Stations
·
ECDB also to be available on DOV website
(password protected)
·
Display format provides all essential information
arranged for case of reference.
•
•
•
•
•
Weekly schedule proposed for data analysis.
Analysed data displayed in MS Access and Oracle.
Query Module designed for and easy retrieval of
RESULTS OF ANALYSIS
Data Range
No. of No. of
Record Record
s
s After
Filterin
g)
01-Jan-05 07-Jan-05 141816 59236
01-Jan-05 15-Jan-05 297536 126525
01-Jan-05 31-Jan-05 608530 247016
% WithKe Cluste Outlier Non
% Of
yword rs
s
Outlier Outlie
Combi
s
rs
nation
42 141782 23711 25778 116004
43 298539 41892 54360 244179
41 551026 68313 100823 450203
18
18
18
ECDB QUERY
ECDB DISPLAY - I
ECDB DISPLAY - II
REPORTS
DATA QUALITY
•
·
•
·
In many cases description of DBK / DEPB entries are
reproduced.
•
·
Drastic steps needed to improve data quality for better
results in data analysis.
•
·
Description and specifications in SB to be verified during
admission.
•
·
Scrutiny and capture of missing information by
Appraising Officers.
•
·
Verification at the time of examination to ensure all
essential details.
•
·
Model/grade/specification.
•
·
Check HS (ITC) classification
Incomplete description and using classification.
EQUIPMENT AND MANPOWER
•
·
Additional resources needed at DOV to
maintain to ECBDB.
•
·
Manpower (1Group A, 2 Group B & 4
Group C).
•
•
Server for data analysis and storage.
•
•
Intranet Server for ICENET
•
•
Webspace (8GB) for internet hosting
•
PCs for staff .
EXPECTED BENEFITS
•
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Online access of analysed expert data to all
departmental officers.
•
·
•
•
Quicker identification of potential cases of valuation
fraud.
•
•
Better monitoring of working of valuation based export
promotion schemes.
•
•
Facilitates risk analysis, targeting and investigations of
export related offences.
•
•
Discourages exporters moving to smaller ports to over
value goods.
•
Provides reports and returns for economic analysis .
Improved quality of export valuation of live exports.
ISSUES FOR DECISION
•
•
•
•
Principle for identification of sensitive commodities
: goods entered for export under claim of DBK, DEPB
or DFRC
•
·
Excluding cases having value caps and specific
rates.
•
•
Schedule for implementation of ECDB (Phase II
and Phase III)
•
•
Additional staffing and equipment required for
ECDB.
Scheme for ECDB data analysis : clustering and
marketing outliers.
DOV
• THANK YOU